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We are searching for the best talent for Director, Omics Enabling Platforms in Spring House, PA.
Purpose: We are seeking a strategic, hands-on leader to build and direct an Omics Enabling organization that integrates omics with automation, robotics, and agentic AI into a unified engine for AI-Native Drug Discovery. The Director will own end-to-end omics capabilities including transcriptomics (bulk & single-cell) delivered through highly automated, robotics-driven workflows that generate robust, scalable, high-dimensional data at speed.
The successful candidate pairs deep expertise in omics technologies with a strong foundation in molecular and cellular biology, enabling interpretation of complex omics datasets and translation of high-dimensional data into biological insights to enable portfolio program decisions. The role combines support for discovery programs with development of reusable, automated experimentation platforms that accelerate learning cycles and generate AI-ready biological data.
You will be responsible for
Own development, optimization, and scaling of discovery-focused assays with a transcriptomics core: bulk RNA-seq, single-cell RNA-seq, WGS/WES and long-read sequencing.
Ensure all assays are automation-ready, reproducible, and standardized for large-scale, perturbational biology.
Generate high-quality, high-dimensional datasets suitable for actionable insights, machine learning and foundation model training.
Drive biological interpretation transforming large-scale data into mechanistic insights, pathway-level understanding, and actionable biological hypotheses.
Automation, Robotics & Autonomous Workflows
Lead the design, deployment, and industrialization of laboratory automation and robotic systems across sample intake, library prep, sequencing, and omics data acquisition.
Build closed-loop, autonomous experimentation workflows with robotic orchestration, scheduling, and minimal manual intervention.
Integrate LIMS/ELN, laboratory execution systems, and QC frameworks to ensure reproducibility, throughput, and traceability.
Continuously drive improvements in cycle time, cost per sample, and scalability through automation.
Agentic AI & Computational Enablement
Partner to establish an agentic AI strategy to automate experimental design, protocol generation, data QC, interpretation, and knowledge capture.
Connect AI agents directly to laboratory execution and robotics platforms to enable active learning cycles.
Maintain validated computational pipelines for alignment, quantification, differential expression, fusion/isoform/splicing detection, and single-cell & omics analytics (batch correction, integration, deconvolution).
Champion adoption of large language models, generative, and multimodal AI within discovery workflows.
Data Engineering & Infrastructure
Own compute strategy (HPC and/or cloud: AWS/GCP/Azure), workflow orchestration (Nextflow/Snakemake/Cromwell), containers, and CI/CD for pipelines.
Build high-throughput pipelines for data acquisition, analytics, and multiomics integration.
Implement FAIR data principles, metadata standards, and privacy/security controls to maximize reuse and AI readiness.
Deliver reusable, versioned data products and dashboards.
People Leadership & Culture
Lead an Omics Enabling organization through direct and matrixed leadership, integrating capabilities across automation, robotics, omics, data engineering, and AI to accelerate AI-Native Drug Discovery.
Foster a culture of safety, quality, scientific excellence, innovation, and rapid learning.
Mentor talent and develop career paths across biology, engineering, and AI disciplines.
Qualifications/Requirements
Education: Minimum of a PhD in Cell Biology, Molecular Biology, Genomics, or a related field, supported by relevant publications is required.
Experience
10+ years of experience in cell biology, omics platforms, and computational biology.
Demonstrated ability to derive biological insights from large-scale omics datasets and communicate findings effectively to multidisciplinary scientific teams
Demonstrated experience leading technical and scientific teams
Technical Skills
Transcriptomics & Omics: Deep expertise in designing, scaling, and industrializing bulk, single-cell, and spatial transcriptomics capabilities. Proven experience building robust, high-throughput data generation platforms that deliver reproducible, high-dimensional biological data for discovery, translational science, and AI-enabled research
Biological Insight Generation: Strong foundation in molecular and cellular biology with demonstrated ability to translate complex transcriptomic data into mechanistic understanding, disease-relevant hypotheses, biomarker strategies, and actionable portfolio decisions. Expertise distinguishing biological signal from technical variation and integrating data across experimental systems and disease contexts.
Automation & robotics: Proven track record building and scaling automated laboratory platforms that integrate robotics, digital orchestration, and closed-loop experimentation to increase throughput, reproducibility, and learning velocity across discovery workflows
Computational & Data Platforms: Deep understanding of modern transcriptomics analytics, reproducible workflow architectures, cloud/HPC computing, and scalable data engineering. Experience defining computational strategies that transform high-dimensional biological data into reusable, analysis-ready, and AI-ready data products.
Digital & Automation Infrastructure: Experience integrating laboratory automation, LIMS/ELN, workflow orchestration, cloud/HPC platforms, and data governance frameworks to enable scalable, reproducible, and AI-ready omics operations. Expertise in FAIR data principles, metadata strategy, platform lifecycle management, and delivery of governed, reusable data assets.
Non-Technical Skills
Strategic thinking with a science-to-impact orientation and crisp communication to technical and executive audiences.
Independent, self-motivated, innovative mindset.
Strong collaboration, planning, prioritization, and problem-solving skills.
Vendor/CRO management and change leadership in fast-moving environments.
We offer a stimulating, collaborative research environment and the opportunity to help shape the technology backbone of AI-Native Drug Discovery.
Johnson & Johnson is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, age, national origin, disability, protected veteran status or other characteristics protected by federal, state or local law. We actively seek qualified candidates who are protected veterans and individuals with disabilities as defined under VEVRAA and Section 503 of the Rehabilitation Act.
Johnson & Johnson is committed to providing an interview process that is inclusive of our applicants’ needs. If you are an individual with a disability and would like to request an accommodation, external applicants please contact us via https://www.jnj.com/contact-us/careers , internal employees contact AskGS to be directed to your accommodation resource.
If you are under 18 years of age you (the candidate) may need to obtain the necessary working papers or other documentation required by state law to start the assignment, as well as get a parent’s consent for the background check.
#LI-Onsite
Required Skills
Preferred Skills
Big Data Management, Collaboration, Data Governance, Data Reporting, Data Savvy, Developing Others, Drug Discovery Development, Health Care Regulation, Inclusive Leadership, Leadership, Molecular Diagnostics, Pharmaceutical Microbiology, Process Improvements, Product Knowledge, Project Reporting, Scientific Research, Strategic Thinking, Sustainability
